In many scientific fields, data analysts analyze raw data and process this raw data to glean useable information. For example, a data analyst can use visual and textual representations of data with analytical operations to explore, understand, and generate hypotheses for evaluation based on this data. As advances have been made in technology that allows data to be gathered in increasingly larger volume and complexity, processing data in an efficient and meaningful manner has become an important and difficult challenge. As data sets become larger and more complex, an increasing amount of expertise may be needed to adequately analyze the raw data to discern useful conclusions. Data analysis in many fields requires a data analyst to have access to expert knowledge both in the domain of the underlying subject matter of the data and also in the techniques uses to process the raw data to derive conclusions.
Adequately trained experts are not always easily available to interpret these increasingly large and complex data sets. Thus, there is a need for assistance in data analysis. Previous attempts to provide assistance for data analysis have not adequately captured the knowledge and experience that an expert data analyst would use when analyzing a large, complex set of data.
Features and advantages of the present disclosure will become more apparent from the detailed description set forth below when taken in conjunction with the drawings, in which like reference characters identify corresponding elements throughout. In the drawings, like reference numbers generally indicate identical, functionally similar, and/or structurally similar elements. The drawing in which an element first appears is indicated by the leftmost digit(s) in the corresponding reference number.